Preparing today’s CRAN package database

Donwload today’s CRAN database

library("cranly")
p_db <- tools::CRAN_package_db()

Clean and organise author names, depends, imports, suggests, enhances

package_db <- clean_CRAN_db(p_db)

The resulting dataset carries the timestamp of when it was put together

attr(package_db, "timestamp")
#> [1] "2018-03-20 09:31:45 GMT"

Network of CRAN packages

Extract edges and nodes for the CRAN package network

package_network <- build_network(object = package_db)

Compute statistics for the package network

## Global package network statistics
package_summaries <- summary(package_network)

Top 10 packages according to various statistics

plot(package_summaries, according_to = "n_imported_by", top = 20)

plot(package_summaries, according_to = "page_rank", top = 20)

plot(package_summaries, according_to = "betweenness", top = 20)

plot(package_summaries, according_to = "n_enhances", top = 20)

plot(package_summaries, according_to = "n_authors", top = 20)

plot(package_summaries, according_to = "n_imports", top = 20)

The sub-network of my packages

my_packages <- package_by(package_network, "Ioannis Kosmidis")
visualize(package_network, package = my_packages)

Build CRAN collaboration network

author_network <- build_network(object = package_db, perspective = "author")

Compute statistics for the collaboration network

author_summaries <- summary(author_network)

Top 10 collaborators according to various network statistics

plot(author_summaries, according_to = "n_packages", top = 20)

plot(author_summaries, according_to = "page_rank", top = 20)

plot(author_summaries, according_to = "betweenness", top = 20)

R Core’s collaboration sub-network

visualize(author_network, author = "R Core")

Brian Ripley’s collaborneion sub-network

visualize(author_network, author = "Brian Ripley")

My collaboration sub-network (much much smaller that the above, of co)

visualize(author_network, author = "Kosmidis")